November 15, 2021
Every conference day consists of three presentation blocks, followed by a keynote talk in the evening. Times are Central European Time (CET). Registered participants will receive a link to Zoom to join the Meeting.
| Time | Presentation |
|---|---|
| 10:30 | Welcome Paul Hünermund, Jermain Kaminski, Carla Schmitt, Beyers Louw Copenhagen Business School & Maastricht University |
| Session 1 | |
| 10:40 | Self-fulfilling Bandits: Endogeneity spillover and dynamic selection in algorithmic decision-making Xiaowei Zhang Hongkong University |
| 10:55 | Off-policy learning of dynamic content promotions Joel Persson ETH Zürich |
| 11:10 | Estimating returns to special education: Combining machine learning and text analysis to address confounding Aurélien Sallin St. Gallen University |
| 11:25 | What’s on the telly? Causality for recommender systems in public-service media corporations Jordi Mur University of Barcelona |
| 11:40 | Q & A |
| 12:00 | 60 min break (Timer) |
| Session 2 | |
| 13:00 | Structural causal models are (solvable by) credal networks Alessandro Antonucci Dalle Molle Institute for Artificial Intelligence Research (IDSIA) |
| 13:15 | Estimating the probabilities of causation via deep monotonic twin networks Ciarán Lee Spotify Research |
| 13:30 | Double machine learning for sample selection models Martin Huber University of Fribourg |
| 13:45 | Positivity violation detection and explainability Hanan Shteingart Vian.ai |
| 14:00 | Q & A |
| 14:20 | 30 min break (Timer) |
| Session 3 | |
| 14:50 | Retrospective causal inference via matrix completion, with an evaluation of the effect of European integration on cross-border employment Jason Poulos Harvard Medical School |
| 15:05 | Crime and mismeasured punishment: Marginal treatment effect with misclassification Vitor Possebom Yale University |
| 15:20 | When should we (not) interpret linear IV estimands as LATE? Tymon Sloczynski Brandeis University |
| 15:35 | Preferences and productivity in organizational matching: Theory and empirics from internal labor markets Bo Cowgill Columbia Business School |
| 15:50 | Q & A |
| 16:10 | 30 min break (Timer) |
| Session 4 | |
| 16:40 | Experimentation and startup performance: Evidence from A/B testing Rem Koning Harvard Business School |
| 16:55 | The paper of how: Estimating treatment effects using the front-door criterion Marc Bellemare University of Minnesota |
| 17:10 | Causal-driven machine learning at Uber scale: A case study Okke van der Wal Uber |
| 17:25 | Generalizing experimental results by leveraging knowledge of mechanisms Carlos Cinelli University of Washington |
| 17:40 | Q & A |
| 18:00 | 30 min break (Timer) |
| Keynote | |
| 18:30 | Keynote Sara Magliacane University of Amsterdam & MIT-IBM Watson AI Lab |
Authors denote presenters. Full author list will be visible in published papers.